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Found 50 papers, 2 papers with code
A CNN-based End-to-End Learning for RIS-assisted Communication System
Numerically we have shown that the bit error rate (BER) performance of the CNN-based autoencoder system is better than the theoretical BER performance of the RIS-assisted communication systems.
Beamforming and Waveform Optimization for RF Wireless Power Transfer with Beyond Diagonal Reconfigurable Intelligent Surfaces
Radio frequency (RF) wireless power transfer (WPT) is a promising technology to seamlessly charge low-power devices, but its low end-to-end power transfer efficiency remains a critical challenge.
Highly Dynamic and Flexible Spatio-Temporal Spectrum Management with AI-Driven O-RAN: A Multi-Granularity Marketplace Framework
Current spectrum-sharing frameworks struggle with adaptability, often being either static or insufficiently dynamic.
Uplink Rate Splitting Multiple Access with Imperfect Channel State Information and Interference Cancellation
Finally, our comparison with non-orthogonal multiple access (NOMA) highlights the outage performance trade-offs between RSMA and NOMA.
Higher-Order Meta Distribution Analysis of Wireless Systems with Application to the Reliability of UWB THz Networks
Communication reliability, as defined by 3GPP, refers to the probability of providing a desired quality of service (QoS).
Interference Prediction Using Gaussian Process Regression and Management Framework for Critical Services in Local 6G Networks
The performance of the proposed approach is evaluated against two benchmarks prediction schemes, a moving average-based estimator and the ideal genie-aided estimator.
A Federated Deep Learning Framework for Cell-Free RSMA Networks
To leverage the distributed nature of the cell-free network, this process is implemented in a Federated Deep Reinforcement Learning (FDRL) structure operating through the cooperation of APs and a central processing unit (CPU).
Beyond Diagonal Reconfigurable Intelligent Surfaces for Multi-Carrier RF Wireless Power Transfer
Motivated by this, we consider a single-input single-output BD-RIS-aided RF-WPT system and we formulate a joint beamforming and waveform optimization problem aiming to maximize the harvested power at the receiver.
Efficient Channel Prediction for Beyond Diagonal RIS-Assisted MIMO Systems with Channel Aging
Moreover, our scheme can deliver a high average downlink sum rate, outperforming other state-of-the-art channel estimation methods.
A Study on Characterization of Near-Field Sub-Regions For Phased-Array Antennas
In this work, we completely characterize the Fraunhofer distance by considering various angles between the PA and the boresight.
Revisiting the Fraunhofer and Fresnel Boundaries for Phased Array Antennas
This paper presents the characterization of near-field propagation regions for phased array antennas, with a particular focus on the propagation boundaries defined by Fraunhofer and Fresnel distances.
Discontinuous Reception with Adjustable Inactivity Timer for IIoT
Specifically, DRX allows the devices to operate in a low-power mode when no data reception is scheduled, and its effectiveness depends on the proper configuration of the DRX parameters.
Practical Challenges for Reliable RIS Deployment in Heterogeneous Multi-Operator Multi-Band Networks
While not an ideal solution, we discuss how ultra-narrowband metasurfaces can be incorporated into the manufacturing of RISs to mitigate some challenges of RIS deployment in wireless networks.
Neural Network-Based Bandit: A Medium Access Control for the IIoT Alarm Scenario
Efficient Random Access (RA) is critical for enabling reliable communication in Industrial Internet of Things (IIoT) networks.
Goal-Oriented Sensor Reporting Scheduling for Non-linear Dynamic System Monitoring
Our proposed GoS utilizes deep reinforcement learning (DRL) with meticulously devised action space, state space, and reward function.
Near-Field Spot Beamfocusing: A Correlation-Aware Transfer Learning Approach
We show through simulations that the proposed scheme improves the training speed about 5 times.
Machine Learning-Based Channel Prediction for RIS-assisted MIMO Systems With Channel Aging
Reconfigurable intelligent surfaces (RISs) have emerged as a promising technology to enhance the performance of sixth-generation (6G) and beyond communication systems.
End-to-End Waveform and Beamforming Optimization for RF Wireless Power Transfer
Radio frequency (RF) wireless power transfer (WPT) is a key technology for future low-power wireless systems.
Deep Reinforcement Learning for Multi-User RF Charging with Non-linear Energy Harvesters
Radio frequency (RF) wireless power transfer (WPT) is a promising technology for sustainable support of massive Internet of Things (IoT).
Malicious RIS versus Massive MIMO: Securing Multiple Access against RIS-based Jamming Attacks
In this letter, we study an attack that leverages a reconfigurable intelligent surface (RIS) to induce harmful interference toward multiple users in massive multiple-input multiple-output (mMIMO) systems during the data transmission phase.
Beyond Diagonal RIS for Multi-Band Multi-Cell MIMO Networks: A Practical Frequency-Dependent Model and Performance Analysis
This paper delves into the unexplored frequency-dependent characteristics of beyond diagonal reconfigurable intelligent surfaces (BD-RISs).
A Bayesian Framework of Deep Reinforcement Learning for Joint O-RAN/MEC Orchestration
In this paper, a joint O-RAN/MEC orchestration using a Bayesian deep reinforcement learning (RL)-based framework is proposed that jointly controls the O-RAN functional splits, the allocated resources and hosting locations of the O-RAN/MEC services across geo-distributed platforms, and the routing for each O-RAN/MEC data flow.
6G Fresnel Spot Beamfocusing using Large-Scale Metasurfaces: A Distributed DRL-Based Approach
However, obtaining exact CSI for ELPMs is not feasible in all environments; we alleviate this by proposing an adaptive novel CSI-independent ML scheme based on the TD3 deep-reinforcement-learning (DRL) method.
Generative AI-Based Probabilistic Constellation Shaping With Diffusion Models
This way, we make the constellation symbols sent by the transmitter, and what is inferred (reconstructed) at the receiver become as similar as possible, resulting in as few mismatches as possible.
Conditional Denoising Diffusion Probabilistic Models for Data Reconstruction Enhancement in Wireless Communications
In this paper, conditional denoising diffusion probabilistic models (DDPMs) are proposed to enhance the data transmission and reconstruction over wireless channels.
GDOP Based BS Selection for Positioning in mmWave 5G NR Networks
We propose a BS selection algorithm for UE positioning based on the GDOP of the BSs participating in the positioning process.
On the Radio Stripe Deployment for Indoor RF Wireless Power Transfer
One of the primary goals of future wireless systems is to foster sustainability, for which, radio frequency (RF) wireless power transfer (WPT) is considered a key technology enabler.
Diffusion Models for Wireless Communications
In this article, we outline the applications of diffusion models in wireless communication systems, which are a new family of probabilistic generative models that have showcased state-of-the-art performance.
Decomposition Based Interference Management Framework for Local 6G Networks
Managing inter-cell interference is among the major challenges in a wireless network, more so when strict quality of service needs to be guaranteed such as in ultra-reliable low latency communications (URLLC) applications.
Waveform Optimization and Beam Focusing for Near-field Wireless Power Transfer with Dynamic Metasurface Antennas and Non-linear Energy Harvesters
Moreover, they demonstrate that increasing the antenna length improves the performance, while DMA outperforms fully-digital architecture in terms of power consumption.
Energy Beamforming for RF Wireless Power Transfer with Dynamic Metasurface Antennas
Radio frequency (RF) wireless power transfer (WPT) is a promising technology for charging the Internet of Things.
Predictive Resource Allocation for URLLC using Empirical Mode Decomposition
It is found that such a decomposition-based prediction method reduces the root mean squared error of the prediction by $20 - 25\%$.
A Learning-Based Trajectory Planning of Multiple UAVs for AoI Minimization in IoT Networks
Many emerging Internet of Things (IoT) applications rely on information collected by sensor nodes where the freshness of information is an important criterion.
Supervised Learning based Sparse Channel Estimation for RIS aided Communications
In the on-grid case, we propose an algorithm to estimate the direct and RIS channels.
A Nonlinear Autoregressive Neural Network for Interference Prediction and Resource Allocation in URLLC Scenarios
Ultra reliable low latency communications (URLLC) is a new service class introduced in 5G which is characterized by strict reliability $(1-10^{-5})$ and low latency requirements (1 ms).
LiDAR Aided Human Blockage Prediction for 6G
Leveraging higher frequencies up to THz band paves the way towards a faster network in the next generation of wireless communications.
Untrained DNN for Channel Estimation of RIS-Assisted Multi-User OFDM System with Hardware Impairments
Further, we have shown that the proposed estimator is robust to interference caused by the hardware impairments at the transceiver and RIS.
Deep Learning-Based Active User Detection for Grant-free SCMA Systems
Grant-free random access and uplink non-orthogonal multiple access (NOMA) have been introduced to reduce transmission latency and signaling overhead in massive machine-type communication (mMTC).
Deep Contextual Bandits for Fast Neighbor-Aided Initial Access in mmWave Cell-Free Networks
Access points (APs) in millimeter-wave (mmWave) and sub-THz-based user-centric (UC) networks will have sleep mode functionality.
Deep Learning-based Power Control for Cell-Free Massive MIMO Networks
Specifically, we model a deep neural network (DNN) and train it in an unsupervised manner to learn the optimum user power allocations which maximize the minimum user rate.
Effective Energy Efficiency of Ultra-reliable Low Latency Communication
Effective Capacity defines the maximum communication rate subject to a specific delay constraint, while effective energy efficiency (EEE) indicates the ratio between effective capacity and power consumption.
Information Theory Information Theory
On the SIR Meta Distribution in Massive MTCNetworks with Scheduling and Data Aggregation
Data aggregation is an efficient approach to handle the congestion introduced by a massive number of machine type devices (MTDs).
Network Slicing for eMBB and mMTC with NOMA and Space Diversity Reception
In this work we study the coexistence in the same Radio Access Network (RAN) of two generic services present in the Fifth Generation (5G) of wireless communication systems: enhanced Mobile BroadBand (eMBB) and massive Machine-Type Communications (mMTC).
Non-Orthogonal Multiple Access and Network Slicing: Scalable Coexistence of eMBB and URLLC
The diverse requirements of these services in terms of data-rates, number of connected devices, latency and reliability can lead to a sub-optimal use of the 5G network, thus network slicing is proposed as a solution that creates customized slices of the network specifically designed to meet the requirements of each service.
On the Optimal Deployment of Power Beacons for Massive Wireless Energy Transfer
In this paper, we investigate the optimal deployment of PBs that guarantees a network-wide energy outage constraint.
Hybrid Beamforming for mm-Wave Massive MIMO Systems with Partially Connected RF Architecture
Hybrid analog-digital beamforming has been recognised as a promising approach for large-scale MIMO implementations with a reduced number of costly and power-hungry RF chains.
Deep Contextual Bandits for Fast Initial Access in mmWave Based User-Centric Ultra-Dense Networks
In this paper, we propose a novel deep contextual bandit (DCB) based approach to perform fast and efficient IA in mmWave based UC UD networks.
Low Complexity Autoencoder based End-to-End Learning of Coded Communications Systems
The newly proposed low complexity autoencoder was capable of achieving a better BER performance than half-rate 16-QAM with hard decision decoding over the full 0-10 dB $E_{b}/N_{0}$ range and a better BER performance than the soft decision decoding in 0-4 dB $E_{b}/N_{0}$ range.
Autonomous Driving without a Burden: View from Outside with Elevated LiDAR
If we are to reduce the effort for the processing units inside the car, we need to uplink the data to edge or an appropriately placed cloud.
Backhaul-Aware Interference Management in the Uplink of Wireless Small Cell Networks
In this paper, a novel, backhaul-aware approach to interference management in wireless small cell networks is proposed.
